Agri Chatbot: Chat-Bot-using-LLM

This project is an agriculture chatbot designed to assist farmers with their queries using a large language model. The chatbot is built with Flask for the backend and uses a pre-trained model from Hugging Face for generating responses.

Features

• Chat Interface: Interact with the chatbot through a user-friendly chat interface.
• Text-to-Speech: Converts the chatbot's responses to audio.
• Responsive Design: Ensures the interface looks good on all devices using Bootstrap.

Getting Started

Prerequisites

• Python 3.7+
• Pip (Python package installer)
• Git (for cloning the repository)
• PyTorch

Installation

1. Clone the repository:

   git clone https://github.com/FaisalAhmedBijoy/Chat-Bot-using-LLM-with-Gradio

2. Install the dependencies:

   pip install -r requirements.txt

3. Download the model:

   Download the Qwen/Qwen2-7B-Instruct model from Hugging Face and place it in a directory (e.g., models).

   python download_model.py

Running the Application

1. Run the Flask application:

   python app.py

2. Open your browser and go to:

   http://127.0.0.1:5000
   

Project Structure

agri-chatbot/
│
├── static/
│   ├── audio/
│   ├── images/
│
├── templates/
│   └── index.html
│
├── .env
├── app.py
├── download_model.py
├── requirements.txt
└── README.md

Demo

Usage

1. Type your query in the input box and press Send.
2. The bot will respond with a text message and an audio message.

Acknowledgments

• The chatbot uses the Qwen2-7B-Instruct model from Hugging Face.
• Flask is used for the web framework.
• Bootstrap is used for styling the web interface.

Contributors

• Faisal Ahmed
• H.M. Mehedi Hasan